Repairing Concavities in ROC Curves

Flach, Peter A. and Wu, Shaomin (2005) Repairing Concavities in ROC Curves. In: IJCAI 05: Nineteenth International Joint Conference on Artificial Intelligence, August 1st, 2005. (Unpublished) (The full text of this publication is not available from this repository)

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Official URL
http://www.ijcai.org/papers/0652.pdf

Abstract

In this paper we investigate methods to detect and repair concavities in ROC curves by manipulating model predictions. The basic idea is that, if a point or a set of points lies below the line spanned by two other points in ROC space, we can use this information to repair the concavity. This effectively builds a hybrid model combining the two better models with an inversion of the poorer models; in the case of ranking classifiers, it means that certain intervals of the scores are identified as unreliable and candidates for inversion. We report very encouraging results on 23 UCI data sets, particularly for naive Bayes where the use of two validation folds yielded significant improvements on more than half of them, with only one loss.

Item Type: Conference or workshop item (Paper)
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Faculties > Social Sciences > Kent Business School > Management Science
Depositing User: Shaomin Wu
Date Deposited: 28 Nov 2012 11:59
Last Modified: 17 Apr 2014 09:39
Resource URI: http://kar.kent.ac.uk/id/eprint/32217 (The current URI for this page, for reference purposes)
ORCiD (Flach, Peter A.):
ORCiD (Wu, Shaomin):
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